Using appropriate methods to assess population exposure to extreme weather events: Why and how?

The existing assessment of population exposure to extreme weather events has established various standards, particularly in the definitions of extreme weather events and the methods of population exposure assessment, hindering reliable risk perception. This study reviews three core threshold types for defining extreme weather events (absolute, relative and composite) and three major population exposure assessment methods (static, dynamic and alternative indicator-based), analysing their advantages, disadvantages and applicability. These findings demonstrate that the multi-factorial composite threshold can reflect the health-related risks of extreme weather events from a multi-dimensional perspective, promoting a paradigm shift from ‘weather-centric theory’ to ‘impact-centric theory’ in related research. Meanwhile, dynamic population exposure assessment based on real-time spatiotemporal behavioural responses of the population is the core innovation direction to break through the limitations of static assessment and improve the accuracy of exposure quantification. This study also identifies key research limitations in the current field, including non-standardised and non-multi-factorial definitions of extreme weather events, methodological biases inherent in exposure assessment, inadequate integration of population vulnerability and adaptability dimensions and limited applicability of the assessment system in data-scarce regions. Thus, by clarifying the necessity of scientific assessment and adopting targeted strategies—promoting the standardisation and multi-factorial transformation of extreme weather event definitions, optimising the methodological system of population exposure assessment and constructing an integrated assessment framework of exposure–vulnerability–adaptability—we can bridge the gap between scientific research and practical application, and improve the scientific rigour and effectiveness of the assessment of population exposure to extreme weather events.